1. Temporal Databases

2. Outline Spatial Databases Temporal Databases Spatio-temporal ….
Indexing, Query processing
Temporal Databases
Spatio-temporal ….

3. Temporal DBs – Motivation
Conventional databases represent the state of an enterprise at a single moment of time
Many applications need information about the past
Financial (payroll)
Medical (patient history)
Government
Temporal DBs: a system that manages time varying data

4. Comparison Conventional DBs:
Evolve through transactions from one state to the next
Changes are viewed as modifications to the state
No information about the past
Snapshot of the enterprise
Temporal DBs:
Maintain historical information
Changes are viewed as additions to the information stored in the database
Incorporate notion of time in the system
Efficient access to past states

5. Temporal Databases
Temporal Data Models: extension of relational model by adding temporal attributes to each relation
Temporal Query Languages: TQUEL, SQL3
Temporal Indexing Methods and Query Processing

6. Taxonomy of time Transaction time databases
Transaction time is the time when a fact is stored in the database
Valid time databases:
Valid time is the time that a fact becomes effective in reality
Bi-temporal databases:
Support both notions of time

7. Example
Sales example: data about sales are stored at the end of the day
Transaction time is different than valid time
Valid time can refer to the future also!
Credit card: 03/01-04/06

8. Transaction Time DBs
Time evolves discretely, usually is associated with the transaction number:
A record R is extended with an interval [t.start, t.end). When we insert an object at t1 the temporal attributes are updated -> [t1, now)
Updates can be made only to the current state!
Past cannot be changed
“Rollback” characteristics
T1 -> T2 -> T3 -> T4 ….

9. Transaction Time DBs Deletion is logical (never physical deletions!)
When an object is deleted at t2, its temporal attribute changes from [t1, now)  [t1, t.t2) (lifetime)
Object is “alive” from insertion to deletion time, ex. t1 to t2. If “now” then the object is still alive
eid
salary
start
end 10
20K
9/93
10/94 20
50K
4/94 * 33
30K
5/94
6/95
1/95
time

10. Transaction Time DBs id
Database evolves through insertions and deletions

11. Transaction Time DBs Requirements for index methods:
Store past logical states
Support addition/deletion/modification changes on the objects of the current state
Efficiently access and query any database state

12. Transaction Time DBs Queries:
Timestamp (timeslice) queries: ex. “Give me all employees at 05/94”
Range-timeslice: “Find all employees with id between 100 and 200 that worked in the company on 05/94”
Interval (period) queries: “Find all employees with id in [100,200] from 05/94 to 06/96”

13. Valid Time DBs Time evolves continuously
Each object is a line segment representing its time span (eg. Credit card valid time)
Support full operations on interval data:
Deletion at any time
Insertion at any time
Value change (modification) at any time (no ordering)

14. Valid Time DBs Deletion is physical:
No way to know about the previous states of intervals
The notion of “future”, “present” and “past” is relative to a certain timestamp t

15. Valid Time DBs
The reality “best know now !”

16. Valid Time DBs Requirements for an Index method:
Store the latest collection of interval-objects
Support add/del/mod changes to this collection
Efficiently query the intervals in the collection
Timestamp query
Interval (period) query

17. Bitemporal DBs
A transaction-time Database, but each record is an interval (plus the other attributes of the record)
Keeping the evolution of a dynamic collection of interval-objects
At each timestamp, it is a valid time database

18. Bitemporal DBs

19. Bitemporal DBs Requirements for access methods:
Store past/logical states of collections of objects
Support add/del/mod of interval objects of the current logical state
Efficient query answering